The rapid development and popularization of mobile terminals such as mobile phones and handheld computers have brought about the emergence and rapid development of indoor (or local region) positioning technology, which mainly integrates a number of technologies, such as wireless communication, base station positioning and inertial navigation positioning, etc., to form an indoor position positioning system for monitoring the positions of people, objects and the like in an indoor space. This positioning technology has a widespread need and application in a variety of fields, e.g., commercial applications, public security and military scenarios.
Currently, mainstream indoor positioning technology primarily relies on a wireless beacon (e.g., Bluetooth, WiFi, etc.) or a scenario image to carry out a feature matching to determine an initial position or a reference position, and perform adjustments of positioning points with the help of gait navigation, inertial navigation, etc. This type of mainstream indoor positioning technology, however, has problems of high overhead for device deployment, high power consumption of mobile devices (wireless beacon mode), and complicated and inaccurate positioning algorithm (scenario image mode). For positioning technology using a scenario image, scenario images of locations are captured, and image features and location information are recorded during collection to establish a feature-position database. Moreover, during the positioning, an image of a current location is captured, and features thereof are extracted and compared with features in the feature database to determine a current position.